c17hawke / simple-dvc-demo Goto Github PK

Python 28.13% Jupyter Notebook 52.19% CSS 0.09% HTML 19.54% Procfile 0.05%

simple-dvc-demo's Introduction

create env

conda create -n wineq python=3.7 -y

activate env

conda activate wineq

created a req file

install the req

pip install -r requirements.txt

download the data from

https://drive.google.com/drive/folders/18zqQiCJVgF7uzXgfbIJ-04zgz1ItNfF5?usp=sharing

git init

dvc init

dvc add data_given/winequality.csv

git add .

git commit -m "first commit"

oneliner updates for readme

git add . && git commit -m "update Readme.md"

git remote add origin https://github.com/c17hawke/simple-dvc-demo.git
git branch -M main
git push origin main

tox command -

tox

for rebuilding -

tox -r

pytest command

pytest -v

setup commands -

pip install -e .

build your own package commands-

python setup.py sdist bdist_wheel

simple-dvc-demo's People

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simple-dvc-demo's Issues

I have run into a problem

In the conftest.py file:

import pytest
import yaml
import os
import json

@pytest.fixture
def config(config_path="params.yaml"):
with open(config_path) as yaml_file:
config = yaml.safe_load(yaml_file)
return config

@pytest.fixture
def schema_in(schema_path="schema_in.json"):
with open(schema_path) as json_file:
schema = json.load(json_file)
return schema

when i push it to github in Action get the error:

please help

Facing error for dvc repro after log_production_model.py file creation..

here is the code log_production_model.py file

from src.get_data import read_params
import argparse
import mlflow
from mlflow.tracking import MlflowClient
from pprint import pprint
import joblib
import os

def log_production_model(config_path):
config = read_params(config_path)

mlflow_config = config["mlflow_config"] 


model_name = mlflow_config["registered_model_name"]


remote_server_uri = mlflow_config["remote_server_uri"]

mlflow.set_tracking_uri(remote_server_uri)


runs = mlflow.search_runs(experiment_ids=1)
lowest = runs["metrics.mae"].sort_values(ascending=True)[0]
lowest_run_id = runs[runs["metrics.mae"] == lowest]["run_id"][0]


client = MlflowClient()
for mv in client.search_model_versions(f"name='{model_name}'"):
    mv = dict(mv)
    
    if mv["run_id"] == lowest_run_id:
        current_version = mv["version"]
        logged_model = mv["source"]
        pprint(mv, indent=4)
        client.transition_model_version_stage(
            name=model_name,
            version=current_version,
            stage="Production"
        )
    else:
        current_version = mv["version"]
        client.transition_model_version_stage(
            name=model_name,
            version=current_version,
            stage="Staging"
        )        


loaded_model = mlflow.pyfunc.load_model(logged_model)

model_path = config["webapp_model_dir"] #"prediction_service/model"

joblib.dump(loaded_model, model_path)

if name == 'main':
args = argparse.ArgumentParser()
args.add_argument("--config", default="params.yaml")
parsed_args = args.parse_args()
data = log_production_model(config_path=parsed_args.config)

Here the error which i am getting when i try to run dvc repro.. i think in video tutorial you were also faced the same issue but i don't how did you solve.. please help me out.

mlflow page not opening

http://0.0.0.0:1234 not working. I follow every sept as given

c17hawke / simple-dvc-demo Goto Github PK

simple-dvc-demo's Introduction

simple-dvc-demo's People

Stargazers

Watchers

Forkers

simple-dvc-demo's Issues

I have run into a problem

Facing error for dvc repro after log_production_model.py file creation..

mlflow page not opening

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